Tailoring electromagnetic absorption performances of TiO2/Co/carbon nanofibers through tuning graphitization degrees

Low density, high stability and strong dielectric loss capacity endow carbon-based nanocomposites with superb microwave dissipation performances. Different from grapheme or carbon nanotubes, the graphitization degrees of carbon-based composites derived from the organic precursor pyrolysis can be accurately regulated by controlling the carbonization temperature. As such, their electromagnetic properties can be easily tuned. In this work, we report the preparation of TiO₂/Co/Carbon nanofibers (CNFs) through a combined approach of electrospun and carbonization at different temperatures. The nanofibers with an average diameter of 300 nm were coated by a dense layer of TiO₂ and embedded by Co/CoO nanoparticles. The performance evaluation indicated the composite obtained at 700 °C exhibits remarkably strong absorption of −63.2 dB at 9.8 GHz and wide effective absorption bandwidth of 6.4 GHz with a pretty low filling rate of 15 wt%. Further analysis on the electromagnetic behaviors shows that the composite possesses regulable impedance matching characteristic and absorption performances, implying the huge application potential under various demand conditions.     

Design and locomotion analysis of two kinds of rolling expandable mobile linkages with a single degree of freedom

Frontiers of Mechanical Engineering - This study presents two kinds of rolling robots that are able to roll by deforming their outer shapes with a single degree of freedom. Each robot is an...     

Environmental economic dispatch in multi-area power system employing improved differential evolution with fuzzy selection

In a deregulated multi-area electrical power system the objective is to determine the most economical generation dispatch strategy that could satisfy the area load demands, the tie-line limits and other operating constraints. Usually, economic dispatch (ED) deals only with the cost minimization, but minimization of emission content has also become an equally important concern due to the mandatory requirement of pollution reduction for environmental protection. Environmental economic dispatch (EED) is a complex multi-objective optimization (MOO) problem with conflicting goals. Normally a fuzzy ranking is employed to rank the large number of Pareto solutions obtained after solving a MOO problem. But in this paper the preference of the decision maker (DM) is used to guide the search and to select the population for the next generation. An improved differential evolution (DE) method is proposed where the selection operation is modified to reduce the complexity of multi-attribute decision making with the help of a fuzzy framework. Solutions are assigned a fuzzy rank on the basis of their level of satisfaction for different objectives before the population selection and then the fuzzy rank is used to select and pass on better solutions to the next generation. A well distributed Pareto-front is obtained which presents a large number of alternate trade-off solutions for the power system operator. A momentum operation is also included to prevent stagnation and to create Pareto diversity. Studies are carried out on three test cases and results obtained are found to be better than some previous literature.     

Study on maximum power point tracking of photovoltaic array in irregular shadow

Traditional maximum power point tracking (MPPT) methods can hardly find global maximum power point (MPP) because output characteristics curve of photovoltaic (PV) array may have multi local maximum power points in irregular shadow, and thus easily fall into the local maximum power point. To address this drawback, Considering that sliding mode variable structure (SMVS) control strategy have such advantages as simple structure, fast response and strong robustness, and P&O method have the advantages of simple principle and convenient implementation, so a new algorithm combining SMVS control method and P&O method is proposed, besides, PI controller is applied to reduce system chattering caused by switching sliding surface. It is applied to MPPT control of PV array in irregular shadow to solve the problem of multi-peak optimization in partial shadow. In order to verity the rationality of the proposed algorithm, the experimental circuit is built, which achieves MPPT control by means of the proposed algorithm and P&O method. The experimental results show that compared with the traditional P&O algorithm, the proposed algorithm can fast track the global MPP, tracking speed increases by 60% and the relative error decreased by 20%. Moreover, the system becomes more stable near the MPP, the fluctuations of output power is greatly reduced, and thus make full use of solar energy.     

A control matching model predictive control approach to string stable vehicle platooning

A predictive control strategy for vehicle platoons is presented in this paper, accommodating both string stability and constraints (e.g., physical and safety) satisfaction. In the proposed design procedure, the two objectives are achieved by matching a model predictive controller (MPC), enforcing constraints satisfaction, with a linear controller designed to guarantee string stability. The proposed approach neatly combines the straightforward design of a string stable controller in the frequency domain, where a considerable number of approaches have been proposed in literature, with the capability of an MPC-based controller enforcing state and input constraints.A controller obtained with the proposed design procedure is validated both in simulations and in the field test, showing how string stability and constraints satisfaction can be simultaneously achieved with a single controller. The operating region that the MPC controller is string stable is characterized by the interior of feasible set of the MPC controller.     

Precise gouging-free tool orientations for 5-axis CNC machining

We present a precise approach to the generation of optimized collision-free and gouging-free tool paths for 5-axis CNC machining of freeform NURBS surfaces using flat-end and rounded-end (bull nose) tools having cylindrical shank. To achieve high approximation quality, we employ analysis of hyper-osculating circles (HOCs) (Wang et al., 1993a,b), that have third order contact with the target surface, and lead to a locally collision-free configuration between the tool and the target surface. At locations where an HOC is not possible, we aim at a double tangential contact among the tool and the target surface, and use it as a bridge between the feasible HOC tool paths. We formulate all such possible two-contact configurations as systems of algebraic constraints and solve them. For all feasible HOCs and two-contact configurations, we perform a global optimization to find the tool path that maximizes the approximation quality of the machining, while being gouge-free and possibly satisfying constraints on the tool tilt and the tool acceleration. We demonstrate the effectiveness of our approach via several experimental results.     

Real-time administration of tool sharing and best matching to enhance assembly lines balanceability and flexibility

Collaboration has been found in previous studies on the design of assembly lines to be a useful mechanism. In this study, the focus is on a collaborative assembly (CA) framework, inspired by the design principles of CCT, the Collaborative Control Theory, to improve balanceability and flexibility of assembly lines through tool sharing (TS) among idle and bottleneck workstations. TS is widely practiced in advanced assembly facilities to reduce cost and improve consistency and standardization in assembly and in assembly-and-test utilities, relying often on real time control. The framework developed here addresses the systems design aspect of Mechatronics, covering the planning, execution, and control mechanisms. Planning includes assembly line balancing (ALB) and initial TS decisions, made continually by solving a bi-objective mixed-integer program (BOMIP). A collaborative multi-agent system (CMAS) enhanced with a TS-best matching (BM) protocol is developed to execute the plan, control the process, and modify the TS decisions, considering dynamic changes in the system’s operations. Experiments show that the new CA framework significantly outperforms classic approaches (i.e., ALB without TS-BM) in terms of cycle time, utilization of tools, and balanceability. In addition, the control mechanism is proven to augment the line’s flexibility against the inherent uncertainties of assembly processes, compared to the previously developed static CA frameworks.